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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 recipes to build intelligent machine learning systems with the power of Python

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789131680
Length 422 pages
Edition 2nd Edition
Languages
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Authors (2):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Nick McClure Nick McClure
Author Profile Icon Nick McClure
Nick McClure
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. The TensorFlow Way 3. Linear Regression 4. Support Vector Machines 5. Nearest-Neighbor Methods 6. Neural Networks 7. Natural Language Processing 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Taking TensorFlow to Production 11. More with TensorFlow 12. Other Books You May Enjoy

Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are responsible for the major breakthroughs in image recognition made in the past few years. In this chapter, we will cover the following topics:

  • Implementing a simple CNN
  • Implementing an advanced CNN
  • Retraining existing CNN models
  • Applying Stylenet and the neural-style project
  • Implementing DeepDream
As a reminder, the reader can find all of the code for this chapter available online here: https://github.com/nfmcclure/tensorflow_cookbook , as well as the Packt repository: https://github.com/PacktPublishing/TensorFlow-Machine-Learning-Cookbook-Second-Edition.
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